Biology subjects

Heyne, S.

Publications and source records attributed to Heyne, S..

5 recordsLinked to original sources

bioRxiv2023

Identification of two β-cell subtypes by 7 independent criteria

Despite the recent explosion in surveys of cell-type heterogeneity, the mechanisms that specify and stabilize highly related cell subtypes remain poorly understood. Here, focusing initially on exploring quantitative histone mark heterogeneity, we identify two major sub-types of pancreatic {beta}-cells ({beta}HI and {beta}LO). {beta}HI and {beta}LO cells differ in their size, morphology, cytosolic and nuclear ultrastructure, transcriptional output, epigenomes, cell surface marker, and function. Importantly, {beta}HI and {beta}LO cells can be FACS separated live into CD24+ ({beta}HI) and CD24- ({beta}LO) fractions. From an epigenetic viewpoint, {beta}HI-cells exhibit [~]4-fold higher levels of H3K27me3, more compacted chromatin, and distinct chromatin organization that associates with a specific pattern of transcriptional output. Functionally, {beta}HI cells have increased mitochondrial mass, activity, and insulin secretion both in vivo and ex vivo. Critically, Eed and Jmjd3 loss-of-function studies demonstrate that H3K27me3 dosage is a significant regulator of {beta}HI / {beta}LO cell ratio in vivo, yielding some of the first-ever specific models of {beta}-cell sub-type distortion. {beta}HI and {beta}LO sub-types are conserved in humans with {beta}HI-cells enriched in human Type-2 diabetes. These data identify two novel and fundamentally distinct {beta}-cell subtypes and identify epigenetic dosage as a novel regulator of {beta}-cell subtype specification and heterogeneity. HighlightsO_LIQuantitative H3K27me3 heterogeneity reveals 2 common {beta}-cell subtypes C_LIO_LI{beta}HI and {beta}LO cells are stably distinct by 7 independent sets of parameters C_LIO_LIH3K27me3 dosage controls {beta}HI / {beta}LO ratio in vivo C_LIO_LI{beta}HI and {beta}LO cells are conserved in humans and enriched in Type-2 diabetes C_LI

cell biology↗

bioRxiv2019

Empowering the annotation and discovery of structured RNAs with scalable and accessible integrative clustering

RNA plays essential regulatory roles in all known forms of life. Clustering RNA sequences with common sequence and structure is an essential step towards studying RNA function. With the advent of high-throughput sequencing techniques, experimental and genomic data are expanding to complement the predictive methods. However, the existing methods do not effectively utilize and cope with the immense amount of data becoming available. Here we present GraphClust2, a comprehensive approach for scalable clustering of RNAs based on sequence and structural similarities. GraphClust2 provides an integrative solution by incorporating diverse types of experimental and genomic data in an accessible fashion via the Galaxy framework. We demonstrate that the tasks of clustering and annotation of structured RNAs can be considerably improved, through a scalable methodology that also supports structure probing data. Based on this, we further introduce an off-the-shelf procedure to identify locally conserved structure candidates in long RNAs. In this way, we suggest the presence and the sparsity of phylogenetically conserved local structures in some long non-coding RNAs. Furthermore, we demonstrate the advantage of a scalable clustering for discovering structured motifs under inherent and experimental biases and uncover prominent targets of the double-stranded RNA binding protein Roquin-1 that are evolutionary conserved.

bioinformatics↗

bioRxiv2018

CRUP: A comprehensive framework to predict condition-specific regulatory units

We present the software CRUP (Condition-specific Regulatory Units Prediction) to infer from epigenetic marks a list of regulatory units consisting of dynamically changing enhancers with their target genes. The workflow consists of a novel pre-trained enhancer predictor that can be reliably applied across cell lines and species, solely based on histone modification ChIP-seq data. Enhancers are subsequently assigned to different conditions and correlated with gene expression to derive regulatory units. We thoroughly test and then apply CRUP to a rheumatoid arthritis model, identifying enhancer-gene pairs comprising known disease genes as well as new candidate genes.\n\nAvailabilityhttps://github.com/VerenaHeinrich/CRUP

bioinformatics↗

bioRxiv2018

snakePipes enable flexible, scalable and integrative epigenomic analysis

The scale and diversity of epigenomics data has been rapidly increasing and ever more studies now present analyses of data from multiple epigenomic techniques. Performing such integrative analysis is time-consuming, especially for exploratory research, since there are currently no pipelines available that allow fast processing of datasets from multiple epigenomic assays while also allow for flexibility in running or upgrading the workflows. Here we present a solution to this problem: snakePipes, which can process and perform downstream analysis of data from all common epigenomic techniques (ChIP-seq, RNA-seq, Bisulfite-seq, ATAC-seq, Hi-C and single-cell RNA-seq) in a single package. We demonstrate how snakePipes can simplify integrative analysis by reproducing and extending the results from a recently published large-scale epigenomics study with a few simple commands. snakePipes are available under an open-source license at https://github.com/maxplanck-ie/snakepipes.

genomics↗

bioRxiv2017

The Polycomb-dependent epigenome controls β-cell dysfunction, dedifferentiation and diabetes

Chromatin is the physical template that stabilizes and specifies transcriptional programs. To date, it remains largely unclear to what extent chromatin machinery contributes to the susceptibility and progression of complex diseases. Here, we combined deep epigenome mapping with single cell transcriptomics to mine for evidence of chromatin dysregulation in type-2 diabetes. We identify two chromatin-state signatures that track the trajectory of {beta}-cell dysfunction in mice and humans: ectopic activation of bivalent Polycomb-domains and a loss of expression at a subclass of highly active domains containing key lineage-defining genes. {beta}-cell specific deletion of Polycomb (Eed/PRC2) triggers parallel transcriptional signatures. Intriguingly, these {beta}-cell Eed-knockouts also exhibit highly penetrant hyperglycemia-independent dedifferentiation indicating that Polycomb dysregulation sensitizes the {beta}-cell for dedifferentiation. These findings provide novel resources for exploring transcriptional and epigenetic control of {beta}-cell (dys)function. They identify PRC2 as necessary for long-term maintenance of {beta}-cell identity. The data suggest a two-hit model for loss of {beta}-cell identity in diabetes and highlight epigenetic therapeutic potential to block dedifferentiation.

genomics↗